lets_plot.geom_crossbar¶
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lets_plot.geom_crossbar(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, fatten=None, **other_args)¶ Display bars with horizontal median line.
- Parameters
mapping (FeatureSpec) – Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.
data (dict or DataFrame) – The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.
stat (str, default=’identity’) – The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).
position (str or FeatureSpec) – Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.
show_legend (bool, default=True) – False - do not show legend for this layer.
sampling (FeatureSpec) – Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.
tooltips (layer_tooltips) – Result of the call to the layer_tooltips() function. Specifies appearance, style and content.
fatten (float, default=2.5) – A multiplicative factor applied to size of the middle bar.
other_args – Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.
- Returns
Geom object specification.
- Return type
LayerSpec
Note
geom_crossbar() represents a vertical interval, defined by x, ymin, ymax. The mean is represented by horizontal line.
- geom_crossbar() understands the following aesthetics mappings:
x : x-axis coordinates.
ymin : lower bound for error bar.
middle : position of median bar.
ymax : upper bound for error bar.
alpha : transparency level of a layer. Understands numbers between 0 and 1.
color (colour) : color of a geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.
fill : color of geometry filling.
size : lines width.
width : width of a bar.
linetype : type of the line. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.
Examples
>>> from lets_plot import * >>> LetsPlot.setup_html() >>> data = { >>> 'x': ['a', 'b', 'c', 'd'], >>> 'ymin': [5, 7, 3, 5], >>> 'middle': [6.5, 9, 4.5, 7], >>> 'ymax': [8, 11, 6, 9], >>> } >>> ggplot(data, aes(x='x')) + \ >>> geom_crossbar(aes(ymin='ymin', middle='middle', ymax='ymax'))
>>> import numpy as np >>> import pandas as pd >>> from lets_plot import * >>> LetsPlot.setup_html() >>> n = 800 >>> cat_list = {c: np.random.uniform(3) for c in 'abcdefgh'} >>> np.random.seed(42) >>> x = np.random.choice(list(cat_list.keys()), n) >>> y = np.array([cat_list[c] for c in x]) + np.random.normal(size=n) >>> df = pd.DataFrame({'x': x, 'y': y}) >>> err_df = df.groupby('x').agg({'y': ['min', 'median', 'max']}).reset_index() >>> err_df.columns = ['x', 'ymin', 'ymedian', 'ymax'] >>> ggplot() + \ >>> geom_crossbar(aes(x='x', ymin='ymin', middle='ymedian', ymax='ymax', fill='x'), \ >>> data=err_df, width=.6, fatten=5) + \ >>> geom_jitter(aes(x='x', y='y'), data=df, width=.3, shape=1, color='black', alpha=.5)